We use a VGG-like network [1]} pre-trained on AudioSet to extract audio features. Again, the video is split into T=10 clips of one second each without overlapping. For each clip, we extract the output of the last convolutional layer of the network to generate one \(12\times 8 \times 512\)  dimensional feature map.
